Software Engineer; Agentic AI & Cloud Solutions

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

CVS Health is seeking a Staff Software Engineer specializing in developing machine learning solutions using Agentic AI/ML serving as a leader and role model in engineering for both peers and clients. This team is part of the very impactful Claims Adjudication team and this role will be instrumental in our leap to modern AI driven approaches.

The successful candidate will lead project teams working with a diverse range of technologies, including public cloud such as Azure, GCP, on-prem systems such as IBMi and advanced Agentic AI/ML frameworks.

** We will consider remote US for the right candidate

• Able to develop a vision and formulate implementation plans to achieve end goals, evaluating situations, decisions, and issues in the short, medium, and long term.

• Capable of breaking down complex problems, processes, or projects into manageable components for systematic exploration and evaluation.

• Design and implement complex software solutions for APIs, microservices, CI/CD pipelines, and real-time streaming on cloud platforms such as Azure or GCP.

• Conduct research on emerging technologies, design principles, and development frameworks to ensure software solutions remain current, innovative, and future-proof.

• Provide technical guidance in software design and development activities, ensuring clean, scalable, and maintainable code following best practices and design patterns.

• Architect and implement enterprise‑scale Agentic AI solutions leveraging MCP, RAG, reusable Skills, and multi‑agent orchestration frameworks to automate complex business processes, enhance decision‑making, and accelerate digital transformation initiatives.

• Design and optimize AI‑powered platforms utilizing vector databases, semantic search, contextual retrieval, and token‑efficient prompting strategies to deliver scalable, accurate, and cost‑effective Generative AI solutions.

• Establish technical standards and best practices for Model Context Protocol (MCP) integrations, AI Skills development, agent orchestration, memory management, and workflow automation to enable secure and scalable enterprise AI ecosystems.

• Lead the development of intelligent software solutions that combine cloud‑native architectures, modern AI frameworks, Retrieval‑Augmented Generation (RAG), and agentic workflows to improve operational efficiency, developer productivity, and business outcomes.

• Partner with teams across functions and provide expert solutions to multiple complex technical projects/initiatives using interlocking technologies.

• Quickly acquire domain knowledge and build subject matter expertise to advise and guide technical leads and peers.

• Establish and drive execution of technical direction, standards, guidelines, and methodologies, while advocating best practices.

• Lead assigned team projects and mentor junior resources as needed.

• 7+ years of experience as a Software Engineer or combination of machine learning and software engineering with 5+ years leading software development projects, including setting project goals, monitoring progress, tracking milestones, communicating with stakeholders, and mentoring junior developers

• 5+ years of experience developing software using tools like Angular, Java Spring boot, creating cloud native environments in platforms like GCP, Azure or AWS

• 3+ years of Python programming with In‑depth understanding of APIs and microservices‑based architecture and Git and version control

• 2+ years of experience in AI and agentic solution development, including:
  Designing and deploying intelligent agents and autonomous workflows, Integrating AI/ML models into cloud‑native applications. Leveraging LLMs, vector databases, and orchestration…